Unicompartmental knee arthroplasty implant survival in patients with borderline indications.

Introduction: In the literature, 80%-92% of patients are satisfied with their medial femorotibial unicompartmental knee arthroplasties (UKAs). These results are associated with a 10-year implant survival rates ranging from 94% to 98% in various studies. Such outcomes are generally reported after excluding patients with obesity, chronic anterior instability, frontal deformities, or preoperative knee flexion deformities exceeding 10 °.

Could the use of agonist protocols benefit patients who do not respond well to human reproduction treatment?

Objective: The primary goal of this article is to analyze whether there is still room for ovarian stimulation in poor responders prescribed the long protocol.

Methods: This retrospective cohort study analyzed the medical charts of patients seen at the Vida Centro de Fertilidade, a private fertility clinic in Rio de Janeiro, Brazil, from January 2018 to June 2023. It included poor responders described based on the Bologna criteria who were first prescribed conventional treatment with an antagonist protocol, without success, and then the long agonist protocol.

Presumptive Identification of Clinically Significant Hemoglobin Variants Hb E, Hb S, Hb D in Hb A1c Capillary Electrophoresis.

Background: The quantitation of glycated hemoglobin (Hb A1c) represents an average blood glucose level for a period of 2 to 3 months for diagnosing, monitoring, and managing diabetes mellitus. Unreliable results are reported when hemoglobin (Hb) variants are present in the sample. Patients are advised to use an alternate method due to the presence of the variant Hb and a reflex test to Hb electrophoresis to obtain precise information about the Hb variant.

EfficientUNetViT: Efficient Breast Tumor Segmentation Utilizing UNet Architecture and Pretrained Vision Transformer.

This study introduces a sophisticated neural network structure for segmenting breast tumors. It achieves this by combining a pretrained Vision Transformer (ViT) model with a UNet framework. The UNet architecture, commonly employed for biomedical image segmentation, is further enhanced with depthwise separable convolutional blocks to decrease computational complexity and parameter count, resulting in better efficiency and less overfitting.